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Combinatorial testing aims at reducing the cost of software and system testing by reducing the number of test cases to be executed. We propose an approach for combinatorial testing that generates a set of test cases that is as small as possible, using incremental SAT solving. We present several search-space pruning techniques that further improve our approach. Experiments show a significant improvement...
Context-dependent memory studies have indicated that olfaction, the sense of smell, has a special odor memory that can significantly improve recall in some cases. Virtual reality (VR), which has been investigated as a training tool, could feasibly benefit from odor memory by incorporating olfactory stimuli. There have been a few studies on this concept for semantic learning, but not for procedural...
With the introduction of laptops, I-phones and world wide web it has become very easy for everyone to assess the information and so much so that the people have started reading newspapers on the run. The set of websites of Punjabi and Hindi newspapers has been prepared. There are sixty three websites of Punjabi and eighty four websites of Hindi newspapers all over the world. Five software tools have...
Content Based Video Classification is becoming necessary for various video analysis applications to be able to handle humongous amounts of video data being generated & shared all over the Internet. This paper proposes use of DTTBTC for color based feature extraction from video key frames which are used by machine learning classifiers for training & testing. Experimental results show accuracy...
Phasor measurement units (PMUs) are being increasingly deployed to improve monitoring and control of the power grid due to their improved data synchronization and reporting rates in comparison with legacy metering devices. However, one drawback of their higher data rates is the associated increase in bandwidth (for transmission) and storage requirements (for data archives). Fortunately, typical grid...
We present an algorithm, Sparse Atomic Feature Learning (SAFL), that transforms noisy labeled datasets into a sparse domain by learning atomic features of the underlying signal space via gradient minimization. The sparse signal representations are highly compressed and cleaner than the original signals. We demonstrate the effectiveness of our techniques on fMRI activity patterns. We produce low-dimensional,...
3D-HEVC is the latest 3D video project of MPEG for 3D video coding. To compress the depth videos in 3D-HEVC efficiently, depth distortion models considering the distortions in synthesized views have been introduced. However, these models introduce a big burden in coding complexity. In this paper, a configuration of depth distortion models applied at each encoding decision stage of 3D-HEVC is proposed...
The paper is dealing with the in-field test of the decode unit of RIS C processors through functional test programs following the SBST approach. The paper details a strategy based on instruction classification and manipulation, and signatures collection. The method does not require the knowledge of detailed implementation information (e.g., the netlist), but is based on the Instruction Set of the...
We initiate a study of learning and testing dynamic environments, focusing on environment that evolve according to a fixed local rule. The (proper) learning task consists of obtaining the initial configuration of the environment, whereas for non-proper learning it suffices to predict its future values. The testing task consists of checking whether the environment has indeed evolved from some initial...
Software Engineering projects typically go through stages of development, with implementation near the end. Following the normal order in a school semester leaves students with little time to develop code and little to show for their efforts besides long written reports. Students also work in a bubble, having little contact with anyone outside their immediate group. This paper describes an innovative...
This paper proposes a structure for a digital coder, optimizing the multiplication circuit area that leads to a substantial gain in the main circuit surface and helps future decoding. The work describes the functioning process, the technical design and tests the coder's main functions. The evolution of RS coding and the growing pallet of application domains are also briefly covered.
The proposed ECG compression method presents the new beat segmentation algorithm. Because this proposed compression method uses the residual difference between original ECG signal beat and the reference ECG beat, the ECG signal must be separated into each beat before doing the compression process. That is the duty of beat segmentation process. Therefore, this process is important step of the selective...
Agility among the software is searching concern during the development phase, as it boost adaptive planning, incremental and evolutionary development with many other features that are lightweight in nature. Security is one of the considerable concern in today's highly agile software development industry. More assertion is on to produce a protected software, so as to lessen the amount of risk and damage...
Agglutinative languages, such as Hungarian, use inflection to modify the meaning of words. Inflection is a string transformation which describe how can a word converted into its inflected form. The transformation can be described by a transformational string. The words can be classified by their transformational string, so inflection is considered as a classification. Linear separability of clusters...
In this article the characteristics of on-bit and one weighted bit sum codes for distortions detection in concurrent error detection systems (CED systems) are described. Conditions under which the weight-based sum code will have all key characteristics of classic Berger code are established. Established features of weight-based sum codes in practice allow to choose the best coding option while organizing...
We implement a learning algorithm for Nonlinear Dynamic State (NDS) Neurons in the framework of Nonlinear Transient Computation (NTC). The learning procedure is based on Spike-Timing Dependent Plasticity (STDP); which maintains the nonlinear dynamics of these neurons so they can perform classification of time varying signals. To expound the practicality of this approach, an example of forgery detection...
Software Maintainability is the business issue in large scale applications and it must be given adequate focus during software development process to minimize the downtime. Inculcating the maintainability features in the software application during its development can minimize the maintainability efforts during its real time use. In that view, this paper presents a new, Maintainable-Software Development...
This paper introduces a hybrid method to synthesize area-efficient fault-secure NoC switches to detect all errors resulting from any single-point combinational or transition fault in switches and interconnect links. Firstly, the structural faults that are always detectable by data encoding at flit-level are identified. Next, the fault-secure structure is constructed with minimized area such that errors...
We report on the behavior of developers working with a live coding environment, which provides information about a program's execution immediately after each change to the source code. The live coding environment we used shows information about each individual source code line, e.g., changed variable values or truth values of conditions. In comparison to developers working in a non-live environment,...
To improve performance, multiprocessor systems implement weak memory consistency models -- and a number of models have been developed over the past years. Weak memory models, however, lead to unforeseen program behavior, and there is a current need for memory model-aware program analysis techniques. The problem is that every memory model calls for new verification algorithms. We study a prominent...
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